This paper proposes a model of financial contagion that accounts for explosive, mutually exciting shocks to market volatility. We fit the model using country-level data during the European sovereign debt crisis, which has its roots in the period 2008–2010, and was continuing to affect global markets as of October, 2011. Our analysis shows that existing volatility models are unable to explain two key stylized features of global markets during presumptive contagion periods: shocks to aggregate market volatility can be sudden and explosive, and they are associated with specific directional biases in the cross-section of country-level returns. Our model repairs this deficit by assuming that the random shocks to volatility are heavy-tailed and correlated cross-sectionally, both with each other and with returns.
We find evidence for significant contagion effects during the major EU crisis periods of May 2010 and August 2011, where contagion is defined as excess correlation in the residuals from a factor model incorporating global and regional market risk factors. Some of this excess correlation can be explained by quantifying the impact of shocks to aggregate volatility in the cross-section of expected returns—but only, it turns out, if one is extremely careful in accounting for the explosive nature of these shocks. We show that global markets have time-varying cross-sectional sensitivities to these shocks, and that high sensitivities strongly predict periods of financial crisis. Moreover, the pattern of temporal changes in correlation structure between volatility and returns is readily interpretable in terms of the major events of the periods in question.

This paper explores integration and contagion among US metropolitan housing markets. The analysis applies Federal Housing Finance Agency (FHFA) house price repeat sales indexes from 384 metropolitan areas to estimate a multi-factor model of U.S. housing market integration. It then identifies statistical jumps in metropolitan house price returns as well as MSA contemporaneous and lagged jump correlations. Finally, the paper evaluates contagion in housing markets via parametric assessment of MSA house price spatial dynamics.

A R-squared measure reveals an upward trend in MSA housing market integration over the 2000s to approximately .83 in 2010. Among California MSAs, the trend was especially pronounced, as average integration increased from about .55 in 1997 to close to .95 in 2008! The 2000s bubble period similarly was characterized by elevated incidence of statistical jumps in housing returns. Again, jump incidence and MSA jump correlations were especially high in California. Analysis of contagion among California markets indicates that house price returns in San Francisco often led those of surrounding communities; in contrast, southern California MSA house price returns appeared to move largely in lock step.

The high levels of housing market integration evidenced in the analysis suggest limited investor opportunity to diversify away MSA-specific housing risk. Further, results suggest that macro and policy shocks propagate through a large number of MSA housing markets. Research findings are relevant to all market participants, including institutional investors in MBS as well as those who regulate housing, the housing GSEs, mortgage lenders, and related financial institutions.

During 1980-2000, an average of 311 companies per year went public in the U.S. Since the technology bubble burst in 2000, the average has been only 102 initial public offerings (IPOs) per year, with the drop especially precipitous among small firms. Many have blamed the Sarbanes-Oxley Act of 2002 and the 2003 Global Settlement’s effects on analyst coverage for the decline in U.S. IPO activity. We offer an alternative explanation. We posit that the advantages of selling out to a larger organization, which can speed a product to market and realize economies of scope, have increased relative to the benefits of remaining as an independent firm. Consistent with this hypothesis, we document that there has been a decline in the profitability of small company IPOs, and that small company IPOs have provided public market investors with low returns throughout the last three decades. Venture capitalists have been increasingly exiting their investments with trade sales rather than IPOs, and an increasing fraction of firms that have gone public have been involved in acquisitions. Our analysis suggests that IPO volume will not return to the levels of the 1980s and 1990s even with regulatory changes.

Stock prices can go down as well as up. Never in financial history has this adage been more apt than on 6 May 2010. Then, the so-called “Flash Crash” sent shocks waves through global equity markets. The Dow Jones experienced its largest ever intraday point fall, losing $1 trillion of market value in the space of half an hour. History is full of such fat-tailed falls in stocks. Was this just another to add to the list, perhaps compressed into a smaller time window?

No. This one was different. For a time, equity prices of some of the world’s biggest companies were in freefall. They appeared to be in a race to zero. Peak to trough, Accenture shares fell by over 99%, from $40 to $0.01. At precisely the same time, shares in Sotheby’s rose three thousand-fold, from $34 to $99,999.99. These tails were not just fatter and faster. They wagged up as well as down.

The Flash Crash left market participants, regulators and academics agog. More than one year on, they remain agog. There has been no shortage of potential explanations. These are as varied as they are many: from fat fingers to fat tails; from block trades to blocked lines; from high-speed traders to low-level abuse. From this mixed bag, only one clear explanation emerges: that there is no clear explanation. To a first approximation, we remain unsure quite what caused the Flash Crash or whether it could recur.

That conclusion sits uneasily on the shoulders. Asset markets rely on accurate pricing of risk. And financial regulation relies on an accurate reading of markets. Whether trading assets or regulating exchanges, ignorance is rarely bliss. It is this uncertainty, rather than the Flash Crash itself, which makes this an issue of potential systemic importance.

In many respects, this uncertainty should come as no surprise. Driven by a potent cocktail of technology and regulation, trading in financial markets has evolved dramatically during the course of this century. Platforms for trading equities have proliferated and fragmented. And the speed limit for trading has gone through the roof. Technologists now believe the sky is the limit.

This rapidly-changing topology of trading raises some big questions for risk management. There are good reasons, theoretically and empirically, to believe that while this evolution in trading may have brought benefits such as a reduction in transaction costs, it may also have increased abnormalities in the distribution of risk and return in the financial system. Such abnormalities hallmarked the Flash Crash. This paper considers some of the evidence on these abnormalities and their impact on systemic risk.

Regulation has thin-sliced trading. And technology has thin-sliced time. Among traders, as among stocks on 6 May, there is a race to zero. Yet it is unclear that this race will have a winner. If it raises systemic risk, it is possible capital markets could be the loser. To avoid that, a redesign of mechanisms for securing capital market stability may be needed.